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The ten completed datasets were then analyzed using SAS Proc MIAnalyze, which combines the dataset-specific results using established methods that provide standard errors, confidence intervals, and p-values properly reflecting imputation of missing data [45].
Completed datasets were obtained from 29 patients.
28 We created 100 imputations, resulting in 100 completed datasets.
Analysis of online respondents was restricted to completed datasets.
We used Rubin rules to average the variable estimates over 60 imputed or completed datasets.
Each missing value was imputed 100 times resulting in 100 completed datasets.
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Data sub-sets are presented as previews for each of the complete datasets.
Chronologically complete datasets are often used in climate variability studies by analyzing data in multiple temporal windows.
For complete datasets, please visit: http://glews.tamu.edu/eastafrica.tamu.edu/eastafrica
Using the procedure described above, we impute m complete datasets.
The complete datasets are available online in Additional file 2, Dataset A1.
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